2025
Robust Transfer Learning for High‐Dimensional GLM Using γ$$ \gamma $$‐Divergence With Applications to Cancer Genomics
Xu F, Ma S, Zhang Q, Xu Y. Robust Transfer Learning for High‐Dimensional GLM Using γ$$ \gamma $$‐Divergence With Applications to Cancer Genomics. Statistics In Medicine 2025, 44: e70170. PMID: 40662636, PMCID: PMC12313224, DOI: 10.1002/sim.70170.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsBreast NeoplasmsComputer SimulationGenomicsHumansLinear ModelsMachine LearningNeoplasmsConceptsTransfer learningReal world biomedical dataRisk of negative transferProximal gradient descentTransfer learning methodTransfer learning approachHigh-dimensional dataHigh-dimensional settingsGradient descentCompetitive performanceLearning methodsEstimation error boundsBiomedical dataEfficient algorithmLearning approachDetection schemeNegative transferAnalysis of complex diseasesDebiasing stepMethod's effectivenessCancer genomic dataData contaminationError boundsHigh-dimensional profiling dataOutliersHierarchical Multi‐Label Classification With Gene‐Environment Interactions in Disease Modeling
Li J, Zhang Q, Ma S, Fang K, Xu Y. Hierarchical Multi‐Label Classification With Gene‐Environment Interactions in Disease Modeling. Statistics In Medicine 2025, 44: e10330. PMID: 39865593, PMCID: PMC12201914, DOI: 10.1002/sim.10330.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsComputer SimulationGene-Environment InteractionHumansLung NeoplasmsModels, StatisticalConceptsHierarchical multi-label classificationMulti-label classificationGene-environment interaction analysisGene-environmentEfficient expectation-maximizationGene-environment interactionsSemi-supervised scenariosCancer Genome AtlasUnlabeled dataInteraction analysisExpectation-maximizationGenome AtlasSuperior performanceHierarchical responseDisease outcomeClassificationPenalized estimatorsPractice settingsDisease modelsBiomedical studiesAnalysis literatureE effects
2024
HEARTSVG: a fast and accurate method for identifying spatially variable genes in large-scale spatial transcriptomics
Yuan X, Ma Y, Gao R, Cui S, Wang Y, Fa B, Ma S, Wei T, Ma S, Yu Z. HEARTSVG: a fast and accurate method for identifying spatially variable genes in large-scale spatial transcriptomics. Nature Communications 2024, 15: 5700. PMID: 38972896, PMCID: PMC11228050, DOI: 10.1038/s41467-024-49846-1.Peer-Reviewed Original ResearchConceptsSpatially variable genesVariable genesSpatial expression patternsSpatial transcriptomics technologiesSpatial transcriptomics researchTranscriptome researchTranscriptomic technologiesBiological functionsExpression patternsSpatial transcriptomicsGenesState-of-the-art methodsColorectal cancer data
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